Airway and Airway Obstruction Site Segmentation Study Using U-Net with Drug-Induced Sleep Endoscopy Images [0.03%]
基于药物诱发睡眠内镜图像的U-Net气道及气道梗阻部位分割研究
Yeong Hun Kang,Jin Youp Kim,Young Jae Kim et al.
Yeong Hun Kang et al.
Obstructive sleep apnea is characterized by a decrease or cessation of breathing due to repetitive closure of the upper airway during sleep, leading to a decrease in blood oxygen saturation. In this study, employing a U-Net model, we utiliz...
Let UNet Play an Adversarial Game: Investigating the Effect of Adversarial Training in Enhancing Low-Resolution MRI [0.03%]
让UNet玩一场对抗游戏：通过对抗训练提高低分辨率MRI效果的研究
Mohammad Javadi,Rishabh Sharma,Panagiotis Tsiamyrtzis et al.
Mohammad Javadi et al.
Adversarial training has attracted much attention in enhancing the visual realism of images, but its efficacy in clinical imaging has not yet been explored. This work investigated adversarial training in a clinical context, by training 206 ...
Neil Chatterjee,Jeffrey Duda,James Gee et al.
Neil Chatterjee et al.
Although numerous AI algorithms have been published, the relatively small number of algorithms used clinically is partly due to the difficulty of implementing AI seamlessly into the clinical workflow for radiologists and for their healthcar...
AutoCorNN: An Unsupervised Physics-Aware Deep Learning Model for Geometric Distortion Correction of Brain MRI Images Towards MR-Only Stereotactic Radiosurgery [0.03%]
自监督物理感知深度学习模型AutoCorNN：用于脑部MRI图像几何失真校正的模型，面向单纯使用磁共振立体定向放射外科手术
Mahboube Sadat Hosseini,Seyed Mahmoud Reza Aghamiri,Ali Fatemi Ardekani et al.
Mahboube Sadat Hosseini et al.
Geometric distortions in brain MRI images arising from susceptibility artifacts at air-tissue interfaces pose a significant challenge for high-precision radiation therapy modalities like stereotactic radiosurgery, necessitating sub-millimet...
TransDiffSeg: Transformer-Based Conditional Diffusion Segmentation Model for Abdominal Multi-Objective [0.03%]
基于变压器的腹部多目标条件扩散分割模型 TransDiffSeg
WenWen Gu,GuoDong Zhang,RongHui Ju et al.
WenWen Gu et al.
In the domain of medical image segmentation, traditional diffusion probabilistic models are hindered by local inductive biases stemming from convolutional operations, constraining their ability to model long-term dependencies and leading to...
3D Features Fusion for Automated Segmentation of Fluid Regions in CSCR Patients: An OCT-based Photodynamic Therapy Response Analysis [0.03%]
基于OCT的光动力疗法反应分析中的CSCR患者液体区域自动化分割的3D特征融合方法
Elena Goyanes,Joaquim de Moura,José I Fernández-Vigo et al.
Elena Goyanes et al.
Central Serous Chorioretinopathy (CSCR) is a significant cause of vision impairment worldwide, with Photodynamic Therapy (PDT) emerging as a promising treatment strategy. The capability to precisely segment fluid regions in Optical Coherenc...
AG-MSTLN-EL: A Multi-source Transfer Learning Approach to Brain Tumor Detection [0.03%]
一种基于多源迁移学习的脑肿瘤检测方法
Shivaprasad Biradar,Virupakshappa
Shivaprasad Biradar
The analysis of medical images (MI) is an important part of advanced medicine as it helps detect and diagnose various diseases early. Classifying brain tumors through magnetic resonance imaging (MRI) poses a challenge demanding accurate mod...
RadImageNet and ImageNet as Datasets for Transfer Learning in the Assessment of Dental Radiographs: A Comparative Study [0.03%]
基于迁移学习的牙科放射线图像评估中的 RadImageNet 和 ImageNet 数据集比较研究
Shota Okazaki,Yuichi Mine,Yuki Yoshimi et al.
Shota Okazaki et al.
Transfer learning (TL) is an alternative approach to the full training of deep learning (DL) models from scratch and can transfer knowledge gained from large-scale data to solve different problems. ImageNet, which is a publicly available la...
MGB-Unet: An Improved Multiscale Unet with Bottleneck Transformer for Myositis Segmentation from Ultrasound Images [0.03%]
改进的多尺度U-Net与瓶颈变换器融合方法在超声图像中用于肌炎分割的方法(MGB-Unet)
Allaa Hussein,Sherin Youssef,Magdy A Ahmed et al.
Allaa Hussein et al.
Myositis is the inflammation of the muscles that can arise from various sources with diverse symptoms and require different treatments. For treatment to achieve optimal results, it is essential to obtain an accurate diagnosis promptly. This...
A Boundary-Enhanced Decouple Fusion Segmentation Network for Diagnosis of Adenomatous Polyps [0.03%]
一种边界增强的解耦融合分割网络的腺瘤息肉诊断方法
Jiaoju Wang,Haoran Feng,Alphonse Houssou Hounye et al.
Jiaoju Wang et al.
Adenomatous polyps, a common premalignant lesion, are often classified into villous adenoma (VA) and tubular adenoma (TA). VA has a higher risk of malignancy, whereas TA typically grows slowly and has a lower likelihood of cancerous transfo...